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| import tensorflow as tf | |
| import streamlit as st | |
| import pandas as pd | |
| from transformers import pipeline | |
| from transformers import AutoTokenizer, TFAutoModelForSequenceClassification | |
| st.title('Sentiment Analyser App') | |
| st.write('Welcome to my sentiment analysis app!') | |
| form = st.form(key='sentiment-form') | |
| user_input = form.text_area('Enter your text') | |
| submit = form.form_submit_button('Submit') | |
| data = ["I love you", "I hate you","We are very hayy to show you that"] | |
| model_name = st.sidebar.selectbox("Select Model",("distilbert-base-uncased-finetuned-sst-2-english", "finiteautomata/bertweet-base-sentiment-analysis")) | |
| #model_name ="distilbert-base-uncased-finetuned-sst-2-english" | |
| #model_name = "finiteautomata/bertweet-base-sentiment-analysis" | |
| #####-------IN LUCRU--------------------------------------- | |
| tokenizer = AutoTokenizer.from_pretrained(model_name) | |
| model = TFAutoModelForSequenceClassification.from_pretrained(model_name) | |
| clf = pipeline("sentiment-analysis", model=model, tokenizer=tokenizer) | |
| #token_ids = tokenizer(data, padding=True, return_tensors='tf') | |
| #out = model(token_ids) | |
| #Y_probas = tf.keras.activations.softmax(out.logits) | |
| #Y_pred = tf.argmax(Y_probas, axis=1) | |
| #print(Y_pred) | |
| ####----------------------------------------------------------- | |
| def parse_input(ui): | |
| SPLIT = ',' | |
| lst = list(ui.split(SPLIT)) | |
| yield lst | |
| dfdict = {} | |
| txtlst = [] | |
| labellst = [] | |
| scorelst = [] | |
| if submit: | |
| model = pipeline(model=model_name) | |
| #lst = list(user_input.split(",")) | |
| #for sentence in lst: | |
| it = parse_input(user_input) #...NICER | |
| for sentence in next(it): | |
| #res = model(sentence) | |
| res = clf(sentence) #...NICER | |
| txtlst.append(sentence) | |
| st.write(sentence) | |
| label = res[0]['label'] | |
| labellst.append(label) | |
| st.write(f'label is {label}') | |
| score = res[0]['score'] | |
| scorelst.append(score) | |
| st.write(f'score = {score}') | |
| dfdict['TEXT'] = txtlst | |
| dfdict['LABEL'] = labellst | |
| dfdict['SCORE'] = scorelst | |
| outdf = pd.DataFrame.from_dict(dfdict) | |
| st.write(outdf) | |
| #result = model(user_input)[0] | |
| #res = model(user_input) | |
| #st.write(result) | |
| #label = result['label'] | |
| #score = result['score'] | |